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Fit for purpose?

An integrative assessment of state-of-the-science downscaling methods


This web page contains information on a multi-institutional project being conducted by researchers at Cornell Univ., NCAR, NOAA/GFDL, and Mitre.org.  The project is supported by funding from the Dept of Defense’s ESTCP program [LINK].   The co-PI for the NOAA GFDL portion of the project is Keith Dixon.

Overview:

Climate risks, such as those associated with increased intensity of precipitation events and sustained changes in extreme temperatures, are factors facing many organizations and individuals with responsibilities for planning decisions on decadal or longer timescales. Risks from a changing climate often are assessed using outputs from Global Climate Models (GCMs), which are bias corrected and downscaled using a plethora of methods, resulting in a potentially paralyzing amount of data. Presented with so many choices of downscaled climate data products that potentially could be used as input to a given climate impacts study, a reasonable question to ask is “Which methods are fit for purpose?”  Unfortunately, there is no one-size-fits-all answer to that question, because of the wide variety of downscaling methods (each with its own performance characteristics) -and- the wide variety of risks that can be considered (each with its own sensitivities to weather and climate factors.)

Our multi-institutional research team consists of accomplished downscaling method developers (statistical, hybrid, and dynamical) and experienced climate system analysts (observations and models.) To address the “Fit for purpose” question, we aim to develop meaningful, objective tests and integrated interpretations to discriminate between downscaling methods.  Our evaluations will include diagnostic measures related to a range of environmental factors (e.g., water resources, heat and health, ecosystem stressors), with additional focus on those of particular interest for select infrastructure applications in the United States. Goals of this project include developing knowledge that will enable risk managers to make better informed decisions on strategic adaptation planning in the face of uncertain climate change impacts, and  communicating that knowledge in multiple ways.  In other words, we seek to develop information and knowledge that can be translated into guidance, so as to better enable practitioners to answer the question of whether, and to what extent, a particular downscaled climate projection data product is “fit for purpose” for a given decision-relevant application.


Research Team Members:

  • Jeffrey Arnold @ ERT corp.
  • Keith Dixon @ NOAA/GFDL
  • Ethan Gutmann @ NCAR
  • Samantha Hartke @ NCAR
  • Flavio Lehner @ Cornell
  • Rachel McCrary @ NCAR
  • Andrew Newman @ NCAR
  • Graham Taylor UCAR/CPAESS @ GFDL
  • Andy Wood @ NCAR
    Consistent with the theme of this project, several research team members participated in the November 2023 workshop
    Understanding Decision-Relevant Regional Climate Projections Workshop
    including as speakers and as part of the workshop’s science organizing committee.